Overview

Dataset statistics

Number of variables14
Number of observations5811
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory266.8 KiB
Average record size in memory47.0 B

Variable types

Numeric13
Categorical1

Alerts

AQI is highly overall correlated with HealthImpactScoreHigh correlation
HealthImpactClass is highly overall correlated with HealthImpactScoreHigh correlation
HealthImpactScore is highly overall correlated with AQI and 1 other fieldsHigh correlation
HealthImpactClass is highly imbalanced (60.1%)Imbalance
PM10 has unique valuesUnique
NO2 has unique valuesUnique
SO2 has unique valuesUnique
Humidity has unique valuesUnique
HospitalAdmissions has 772 (13.3%) zerosZeros

Reproduction

Analysis started2024-07-29 15:11:48.147749
Analysis finished2024-07-29 15:12:09.315112
Duration21.17 seconds
Software versionydata-profiling vv4.6.5
Download configurationconfig.json

Variables

AQI
Real number (ℝ)

HIGH CORRELATION 

Distinct5810
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean248.43848
Minimum0.0058173775
Maximum499.85883
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 KiB
2024-07-29T17:12:09.416108image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.0058173775
5-th percentile25.439463
Q1122.95129
median249.12784
Q3373.63066
95-th percentile475.71866
Maximum499.85883
Range499.853
Interquartile range (IQR)250.67937

Descriptive statistics

Standard deviation144.77763
Coefficient of variation (CV)0.58275045
Kurtosis-1.2066586
Mean248.43848
Median Absolute Deviation (MAD)125.45379
Skewness0.010608134
Sum1443676
Variance20960.564
MonotonicityNot monotonic
2024-07-29T17:12:09.571873image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
365.74823 2
 
< 0.1%
187.2700653 1
 
< 0.1%
35.05406952 1
 
< 0.1%
278.5202637 1
 
< 0.1%
439.6651001 1
 
< 0.1%
84.10182953 1
 
< 0.1%
209.5914307 1
 
< 0.1%
20.95760918 1
 
< 0.1%
413.651062 1
 
< 0.1%
78.40634918 1
 
< 0.1%
Other values (5800) 5800
99.8%
ValueCountFrequency (%)
0.005817377474 1
< 0.1%
0.01535942312 1
< 0.1%
0.06734650582 1
< 0.1%
0.1135191098 1
< 0.1%
0.2989694178 1
< 0.1%
0.3266953826 1
< 0.1%
0.4717076421 1
< 0.1%
0.5560470819 1
< 0.1%
0.6768128872 1
< 0.1%
0.7369110584 1
< 0.1%
ValueCountFrequency (%)
499.8588257 1
< 0.1%
499.7788391 1
< 0.1%
499.7068481 1
< 0.1%
499.6751404 1
< 0.1%
499.4463196 1
< 0.1%
499.3964539 1
< 0.1%
499.1737671 1
< 0.1%
498.967041 1
< 0.1%
498.9104309 1
< 0.1%
498.8746948 1
< 0.1%

PM10
Real number (ℝ)

UNIQUE 

Distinct5811
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148.655
Minimum0.01584808
Maximum299.90195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 KiB
2024-07-29T17:12:09.708505image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.01584808
5-th percentile14.747903
Q175.374954
median147.63499
Q3222.43676
95-th percentile283.01782
Maximum299.90195
Range299.88611
Interquartile range (IQR)147.06181

Descriptive statistics

Standard deviation85.698502
Coefficient of variation (CV)0.57649257
Kurtosis-1.17477
Mean148.655
Median Absolute Deviation (MAD)73.473175
Skewness0.019243203
Sum863834.19
Variance7344.2329
MonotonicityNot monotonic
2024-07-29T17:12:09.846183image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
295.8530273 1
 
< 0.1%
118.0058517 1
 
< 0.1%
290.1639709 1
 
< 0.1%
250.6712189 1
 
< 0.1%
114.9304276 1
 
< 0.1%
89.41275787 1
 
< 0.1%
85.65752411 1
 
< 0.1%
135.1747437 1
 
< 0.1%
166.1825256 1
 
< 0.1%
245.9604492 1
 
< 0.1%
Other values (5801) 5801
99.8%
ValueCountFrequency (%)
0.0158480797 1
< 0.1%
0.0722623542 1
< 0.1%
0.07230140269 1
< 0.1%
0.0728803277 1
< 0.1%
0.1204632074 1
< 0.1%
0.1230868325 1
< 0.1%
0.2150576115 1
< 0.1%
0.2368533313 1
< 0.1%
0.2717505693 1
< 0.1%
0.282912761 1
< 0.1%
ValueCountFrequency (%)
299.901947 1
< 0.1%
299.8515625 1
< 0.1%
299.8381958 1
< 0.1%
299.8005371 1
< 0.1%
299.7621765 1
< 0.1%
299.6714172 1
< 0.1%
299.5852051 1
< 0.1%
299.5682373 1
< 0.1%
299.5680847 1
< 0.1%
299.5263672 1
< 0.1%

PM2_5
Real number (ℝ)

Distinct5809
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.22371
Minimum0.031548917
Maximum199.98497
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 KiB
2024-07-29T17:12:10.015612image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.031548917
5-th percentile9.6684237
Q149.435171
median100.50634
Q3151.34026
95-th percentile190.81539
Maximum199.98497
Range199.95341
Interquartile range (IQR)101.90508

Descriptive statistics

Standard deviation58.096615
Coefficient of variation (CV)0.57966935
Kurtosis-1.205647
Mean100.22371
Median Absolute Deviation (MAD)50.931225
Skewness-0.0028343343
Sum582400
Variance3375.2166
MonotonicityNot monotonic
2024-07-29T17:12:10.193835image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
166.4451599 2
 
< 0.1%
138.6851654 2
 
< 0.1%
13.03856087 1
 
< 0.1%
132.5606232 1
 
< 0.1%
72.87365723 1
 
< 0.1%
137.6818695 1
 
< 0.1%
192.120163 1
 
< 0.1%
171.2488098 1
 
< 0.1%
11.61266804 1
 
< 0.1%
5.290901184 1
 
< 0.1%
Other values (5799) 5799
99.8%
ValueCountFrequency (%)
0.03154891729 1
< 0.1%
0.05049089715 1
< 0.1%
0.06194638461 1
< 0.1%
0.06603185087 1
< 0.1%
0.1108369157 1
< 0.1%
0.1707394868 1
< 0.1%
0.2291901261 1
< 0.1%
0.2407227755 1
< 0.1%
0.2639738023 1
< 0.1%
0.2667278945 1
< 0.1%
ValueCountFrequency (%)
199.9849701 1
< 0.1%
199.9610291 1
< 0.1%
199.8918152 1
< 0.1%
199.8299103 1
< 0.1%
199.7689667 1
< 0.1%
199.75 1
< 0.1%
199.7397003 1
< 0.1%
199.7295837 1
< 0.1%
199.72229 1
< 0.1%
199.6613922 1
< 0.1%

NO2
Real number (ℝ)

UNIQUE 

Distinct5811
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.29345
Minimum0.0096247792
Maximum199.98019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 KiB
2024-07-29T17:12:10.374047image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.0096247792
5-th percentile10.842656
Q153.538538
median102.98774
Q3151.65852
95-th percentile190.59554
Maximum199.98019
Range199.97057
Interquartile range (IQR)98.119978

Descriptive statistics

Standard deviation57.713173
Coefficient of variation (CV)0.56419229
Kurtosis-1.1887739
Mean102.29345
Median Absolute Deviation (MAD)49.118706
Skewness-0.053588707
Sum594427.21
Variance3330.8103
MonotonicityNot monotonic
2024-07-29T17:12:10.531552image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.639263153 1
 
< 0.1%
122.579689 1
 
< 0.1%
197.8729248 1
 
< 0.1%
174.9940338 1
 
< 0.1%
110.4820938 1
 
< 0.1%
163.8795624 1
 
< 0.1%
189.5725555 1
 
< 0.1%
24.94475365 1
 
< 0.1%
24.050354 1
 
< 0.1%
159.9357605 1
 
< 0.1%
Other values (5801) 5801
99.8%
ValueCountFrequency (%)
0.009624779224 1
< 0.1%
0.06141500548 1
< 0.1%
0.1019978002 1
< 0.1%
0.1223270297 1
< 0.1%
0.1983729005 1
< 0.1%
0.1997984499 1
< 0.1%
0.2486877739 1
< 0.1%
0.4161278307 1
< 0.1%
0.4990907311 1
< 0.1%
0.5043523312 1
< 0.1%
ValueCountFrequency (%)
199.9801941 1
< 0.1%
199.9742889 1
< 0.1%
199.9312592 1
< 0.1%
199.8598938 1
< 0.1%
199.7885895 1
< 0.1%
199.765213 1
< 0.1%
199.7388458 1
< 0.1%
199.7307892 1
< 0.1%
199.7050171 1
< 0.1%
199.6503601 1
< 0.1%

SO2
Real number (ℝ)

UNIQUE 

Distinct5811
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.456838
Minimum0.011023181
Maximum99.969559
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 KiB
2024-07-29T17:12:10.665084image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.011023181
5-th percentile5.2050974
Q124.887263
median49.530167
Q373.346615
95-th percentile94.994556
Maximum99.969559
Range99.958534
Interquartile range (IQR)48.459352

Descriptive statistics

Standard deviation28.530329
Coefficient of variation (CV)0.57687329
Kurtosis-1.1687771
Mean49.456838
Median Absolute Deviation (MAD)24.24494
Skewness0.025573891
Sum287393.69
Variance813.97968
MonotonicityNot monotonic
2024-07-29T17:12:10.825294image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.16114807 1
 
< 0.1%
47.82720566 1
 
< 0.1%
76.72885895 1
 
< 0.1%
33.39563751 1
 
< 0.1%
15.89074802 1
 
< 0.1%
40.65991592 1
 
< 0.1%
83.08462524 1
 
< 0.1%
90.41404724 1
 
< 0.1%
90.91742706 1
 
< 0.1%
85.95923615 1
 
< 0.1%
Other values (5801) 5801
99.8%
ValueCountFrequency (%)
0.01102318056 1
< 0.1%
0.01251387596 1
< 0.1%
0.01948623359 1
< 0.1%
0.02408839948 1
< 0.1%
0.02452905104 1
< 0.1%
0.1091541052 1
< 0.1%
0.1242878661 1
< 0.1%
0.1447220594 1
< 0.1%
0.1450316608 1
< 0.1%
0.1652488112 1
< 0.1%
ValueCountFrequency (%)
99.96955872 1
< 0.1%
99.95983887 1
< 0.1%
99.95088196 1
< 0.1%
99.9450531 1
< 0.1%
99.9410553 1
< 0.1%
99.92765045 1
< 0.1%
99.91370392 1
< 0.1%
99.89337158 1
< 0.1%
99.87928772 1
< 0.1%
99.84169769 1
< 0.1%

O3
Real number (ℝ)

Distinct5808
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean149.31243
Minimum0.0016610028
Maximum299.9368
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 KiB
2024-07-29T17:12:10.995821image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.0016610028
5-th percentile15.164336
Q173.999664
median149.55988
Q3223.38013
95-th percentile284.47057
Maximum299.9368
Range299.93515
Interquartile range (IQR)149.38046

Descriptive statistics

Standard deviation86.534241
Coefficient of variation (CV)0.57955148
Kurtosis-1.2061068
Mean149.31243
Median Absolute Deviation (MAD)74.930466
Skewness0.01118201
Sum867654.53
Variance7488.1748
MonotonicityNot monotonic
2024-07-29T17:12:11.145611image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
282.354126 2
 
< 0.1%
269.1383362 2
 
< 0.1%
172.68927 2
 
< 0.1%
265.5737305 1
 
< 0.1%
247.3733826 1
 
< 0.1%
214.9118958 1
 
< 0.1%
131.9894257 1
 
< 0.1%
191.1349792 1
 
< 0.1%
288.5057983 1
 
< 0.1%
170.5977631 1
 
< 0.1%
Other values (5798) 5798
99.8%
ValueCountFrequency (%)
0.001661002752 1
< 0.1%
0.02024929412 1
< 0.1%
0.02927086875 1
< 0.1%
0.1033103988 1
< 0.1%
0.119907774 1
< 0.1%
0.2443851978 1
< 0.1%
0.3081415892 1
< 0.1%
0.3750382662 1
< 0.1%
0.4394979179 1
< 0.1%
0.4571681619 1
< 0.1%
ValueCountFrequency (%)
299.9367981 1
< 0.1%
299.9196167 1
< 0.1%
299.9091492 1
< 0.1%
299.690918 1
< 0.1%
299.6448975 1
< 0.1%
299.6341248 1
< 0.1%
299.6017761 1
< 0.1%
299.5828857 1
< 0.1%
299.5488892 1
< 0.1%
299.5338745 1
< 0.1%

Temperature
Real number (ℝ)

Distinct5810
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.9755
Minimum-9.9909983
Maximum39.963436
Zeros0
Zeros (%)0.0%
Negative1152
Negative (%)19.8%
Memory size22.8 KiB
2024-07-29T17:12:11.301063image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-9.9909983
5-th percentile-7.6434305
Q12.4814998
median14.942428
Q327.465374
95-th percentile37.530075
Maximum39.963436
Range49.954433
Interquartile range (IQR)24.983874

Descriptive statistics

Standard deviation14.483068
Coefficient of variation (CV)0.96711749
Kurtosis-1.2030932
Mean14.9755
Median Absolute Deviation (MAD)12.511754
Skewness0.004898516
Sum87022.628
Variance209.75925
MonotonicityNot monotonic
2024-07-29T17:12:11.480151image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.26694489 2
 
< 0.1%
5.150334835 1
 
< 0.1%
10.71632195 1
 
< 0.1%
8.951398849 1
 
< 0.1%
0.8533828855 1
 
< 0.1%
35.8188591 1
 
< 0.1%
-7.174813747 1
 
< 0.1%
4.633405209 1
 
< 0.1%
36.04862213 1
 
< 0.1%
15.22699451 1
 
< 0.1%
Other values (5800) 5800
99.8%
ValueCountFrequency (%)
-9.990998268 1
< 0.1%
-9.970262527 1
< 0.1%
-9.967556953 1
< 0.1%
-9.965476036 1
< 0.1%
-9.955913544 1
< 0.1%
-9.938031197 1
< 0.1%
-9.935206413 1
< 0.1%
-9.931903839 1
< 0.1%
-9.930357933 1
< 0.1%
-9.920458794 1
< 0.1%
ValueCountFrequency (%)
39.96343613 1
< 0.1%
39.9620285 1
< 0.1%
39.9589386 1
< 0.1%
39.95412827 1
< 0.1%
39.9418869 1
< 0.1%
39.93747711 1
< 0.1%
39.93000412 1
< 0.1%
39.92369461 1
< 0.1%
39.91173553 1
< 0.1%
39.90759277 1
< 0.1%

Humidity
Real number (ℝ)

UNIQUE 

Distinct5811
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.776853
Minimum10.001506
Maximum99.99749
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 KiB
2024-07-29T17:12:11.651508image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum10.001506
5-th percentile14.752562
Q131.995261
median54.543903
Q377.64164
95-th percentile95.42519
Maximum99.99749
Range89.995987
Interquartile range (IQR)45.646379

Descriptive statistics

Standard deviation26.020786
Coefficient of variation (CV)0.47503252
Kurtosis-1.209155
Mean54.776853
Median Absolute Deviation (MAD)22.827192
Skewness0.023062775
Sum318308.29
Variance677.0813
MonotonicityNot monotonic
2024-07-29T17:12:11.818856image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.42434692 1
 
< 0.1%
22.21188354 1
 
< 0.1%
89.72063446 1
 
< 0.1%
70.17338562 1
 
< 0.1%
19.16438293 1
 
< 0.1%
92.37653351 1
 
< 0.1%
54.5261879 1
 
< 0.1%
86.60997772 1
 
< 0.1%
40.4581604 1
 
< 0.1%
58.58655167 1
 
< 0.1%
Other values (5801) 5801
99.8%
ValueCountFrequency (%)
10.00150585 1
< 0.1%
10.00842381 1
< 0.1%
10.05516052 1
< 0.1%
10.1298027 1
< 0.1%
10.13000202 1
< 0.1%
10.15334415 1
< 0.1%
10.16598892 1
< 0.1%
10.16685581 1
< 0.1%
10.16770458 1
< 0.1%
10.18140125 1
< 0.1%
ValueCountFrequency (%)
99.99748993 1
< 0.1%
99.99015045 1
< 0.1%
99.98413849 1
< 0.1%
99.92414093 1
< 0.1%
99.91989899 1
< 0.1%
99.90353394 1
< 0.1%
99.88817596 1
< 0.1%
99.86263275 1
< 0.1%
99.85700989 1
< 0.1%
99.84602356 1
< 0.1%

WindSpeed
Real number (ℝ)

Distinct5810
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9891773
Minimum0.0020942159
Maximum19.99914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 KiB
2024-07-29T17:12:11.957443image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.0020942159
5-th percentile0.92997858
Q14.9523432
median10.051742
Q314.97184
95-th percentile18.91118
Maximum19.99914
Range19.997046
Interquartile range (IQR)10.019497

Descriptive statistics

Standard deviation5.7769499
Coefficient of variation (CV)0.57832089
Kurtosis-1.2130239
Mean9.9891773
Median Absolute Deviation (MAD)5.0089517
Skewness-0.011077888
Sum58047.11
Variance33.37315
MonotonicityNot monotonic
2024-07-29T17:12:12.124019image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.02639389 2
 
< 0.1%
6.137755394 1
 
< 0.1%
8.176369667 1
 
< 0.1%
17.23000145 1
 
< 0.1%
3.692422628 1
 
< 0.1%
12.7224102 1
 
< 0.1%
10.03281689 1
 
< 0.1%
15.75815296 1
 
< 0.1%
8.116394043 1
 
< 0.1%
10.28820324 1
 
< 0.1%
Other values (5800) 5800
99.8%
ValueCountFrequency (%)
0.002094215946 1
< 0.1%
0.00622025039 1
< 0.1%
0.007748259231 1
< 0.1%
0.009946300648 1
< 0.1%
0.01054170076 1
< 0.1%
0.01055687387 1
< 0.1%
0.01118187793 1
< 0.1%
0.01148023363 1
< 0.1%
0.01244941168 1
< 0.1%
0.01256385818 1
< 0.1%
ValueCountFrequency (%)
19.99913979 1
< 0.1%
19.99682617 1
< 0.1%
19.99518394 1
< 0.1%
19.99344635 1
< 0.1%
19.98798752 1
< 0.1%
19.98325157 1
< 0.1%
19.97122192 1
< 0.1%
19.96693611 1
< 0.1%
19.96232605 1
< 0.1%
19.96064568 1
< 0.1%

RespiratoryCases
Real number (ℝ)

Distinct23
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9741869
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-07-29T17:12:12.234002image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q18
median10
Q312
95-th percentile15
Maximum23
Range22
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.1292339
Coefficient of variation (CV)0.31373323
Kurtosis0.09532086
Mean9.9741869
Median Absolute Deviation (MAD)2
Skewness0.25586575
Sum57960
Variance9.7921047
MonotonicityNot monotonic
2024-07-29T17:12:12.342189image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
9 762
13.1%
10 751
12.9%
11 679
11.7%
8 634
10.9%
12 560
9.6%
7 475
8.2%
13 435
7.5%
6 351
6.0%
14 295
 
5.1%
5 238
 
4.1%
Other values (13) 631
10.9%
ValueCountFrequency (%)
1 4
 
0.1%
2 16
 
0.3%
3 48
 
0.8%
4 114
 
2.0%
5 238
 
4.1%
6 351
6.0%
7 475
8.2%
8 634
10.9%
9 762
13.1%
10 751
12.9%
ValueCountFrequency (%)
23 1
 
< 0.1%
22 1
 
< 0.1%
21 4
 
0.1%
20 11
 
0.2%
19 21
 
0.4%
18 41
 
0.7%
17 72
 
1.2%
16 109
 
1.9%
15 189
3.3%
14 295
5.1%

CardiovascularCases
Real number (ℝ)

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9889864
Minimum0
Maximum14
Zeros39
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-07-29T17:12:12.432196image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q13
median5
Q36
95-th percentile9
Maximum14
Range14
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2167915
Coefficient of variation (CV)0.44433704
Kurtosis0.23011702
Mean4.9889864
Median Absolute Deviation (MAD)1
Skewness0.44566381
Sum28991
Variance4.9141644
MonotonicityNot monotonic
2024-07-29T17:12:12.541321image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4 1062
18.3%
5 1033
17.8%
6 864
14.9%
3 813
14.0%
7 577
9.9%
2 448
7.7%
8 376
 
6.5%
1 210
 
3.6%
9 208
 
3.6%
10 107
 
1.8%
Other values (5) 113
 
1.9%
ValueCountFrequency (%)
0 39
 
0.7%
1 210
 
3.6%
2 448
7.7%
3 813
14.0%
4 1062
18.3%
5 1033
17.8%
6 864
14.9%
7 577
9.9%
8 376
 
6.5%
9 208
 
3.6%
ValueCountFrequency (%)
14 6
 
0.1%
13 7
 
0.1%
12 14
 
0.2%
11 47
 
0.8%
10 107
 
1.8%
9 208
 
3.6%
8 376
 
6.5%
7 577
9.9%
6 864
14.9%
5 1033
17.8%

HospitalAdmissions
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0010325
Minimum0
Maximum12
Zeros772
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-07-29T17:12:12.647824image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3987943
Coefficient of variation (CV)0.69903625
Kurtosis0.77095992
Mean2.0010325
Median Absolute Deviation (MAD)1
Skewness0.71532325
Sum11628
Variance1.9566254
MonotonicityNot monotonic
2024-07-29T17:12:12.764572image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 1615
27.8%
1 1552
26.7%
3 1041
17.9%
0 772
13.3%
4 561
 
9.7%
5 179
 
3.1%
6 60
 
1.0%
7 28
 
0.5%
8 2
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
0 772
13.3%
1 1552
26.7%
2 1615
27.8%
3 1041
17.9%
4 561
 
9.7%
5 179
 
3.1%
6 60
 
1.0%
7 28
 
0.5%
8 2
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
8 2
 
< 0.1%
7 28
 
0.5%
6 60
 
1.0%
5 179
 
3.1%
4 561
 
9.7%
3 1041
17.9%
2 1615
27.8%
1 1552
26.7%
0 772
13.3%

HealthImpactScore
Real number (ℝ)

HIGH CORRELATION 

Distinct1528
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.785223
Minimum22.448488
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.8 KiB
2024-07-29T17:12:12.918928image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum22.448488
5-th percentile61.621037
Q198.203056
median100
Q3100
95-th percentile100
Maximum100
Range77.551514
Interquartile range (IQR)1.7969437

Descriptive statistics

Standard deviation13.318905
Coefficient of variation (CV)0.14201496
Kurtosis5.0490422
Mean93.785223
Median Absolute Deviation (MAD)0
Skewness-2.3507092
Sum544985.93
Variance177.39322
MonotonicityNot monotonic
2024-07-29T17:12:13.098271image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 4284
73.7%
76.95124817 1
 
< 0.1%
96.69551086 1
 
< 0.1%
75.65791321 1
 
< 0.1%
92.38387299 1
 
< 0.1%
91.03609467 1
 
< 0.1%
98.74639893 1
 
< 0.1%
72.44568634 1
 
< 0.1%
99.26220703 1
 
< 0.1%
67.97135162 1
 
< 0.1%
Other values (1518) 1518
 
26.1%
ValueCountFrequency (%)
22.44848824 1
< 0.1%
24.5252037 1
< 0.1%
25.50210571 1
< 0.1%
25.97425461 1
< 0.1%
28.20787048 1
< 0.1%
29.12572479 1
< 0.1%
30.07531166 1
< 0.1%
30.36044502 1
< 0.1%
30.39922142 1
< 0.1%
30.47636223 1
< 0.1%
ValueCountFrequency (%)
100 4284
73.7%
99.98575592 1
 
< 0.1%
99.98537445 1
 
< 0.1%
99.9108963 1
 
< 0.1%
99.78769684 1
 
< 0.1%
99.78636932 1
 
< 0.1%
99.73162079 1
 
< 0.1%
99.71383667 1
 
< 0.1%
99.6671524 1
 
< 0.1%
99.63839722 1
 
< 0.1%

HealthImpactClass
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size45.5 KiB
0.0
4808 
1.0
579 
2.0
 
273
3.0
 
95
4.0
 
56

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters17433
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 4808
82.7%
1.0 579
 
10.0%
2.0 273
 
4.7%
3.0 95
 
1.6%
4.0 56
 
1.0%

Length

2024-07-29T17:12:13.239083image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-29T17:12:13.343735image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
0.0 4808
82.7%
1.0 579
 
10.0%
2.0 273
 
4.7%
3.0 95
 
1.6%
4.0 56
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 10619
60.9%
. 5811
33.3%
1 579
 
3.3%
2 273
 
1.6%
3 95
 
0.5%
4 56
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11622
66.7%
Other Punctuation 5811
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10619
91.4%
1 579
 
5.0%
2 273
 
2.3%
3 95
 
0.8%
4 56
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 5811
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17433
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10619
60.9%
. 5811
33.3%
1 579
 
3.3%
2 273
 
1.6%
3 95
 
0.5%
4 56
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17433
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10619
60.9%
. 5811
33.3%
1 579
 
3.3%
2 273
 
1.6%
3 95
 
0.5%
4 56
 
0.3%

Interactions

2024-07-29T17:12:07.294060image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:49.552946image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:51.123091image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:52.478824image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:53.982448image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:55.430458image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:56.858173image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:58.546396image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:59.983340image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:01.399679image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:02.926122image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:04.293652image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:05.835268image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:07.385310image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:49.678466image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:51.222103image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:52.587399image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:54.104805image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:55.534815image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:56.955845image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:58.656464image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:00.101995image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:01.503420image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:03.041571image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:04.401437image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:05.954922image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:07.503762image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:49.814978image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:51.316461image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:52.700632image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:54.209179image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:55.645129image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:57.062340image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:58.767210image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:00.211196image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:01.599881image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:03.141151image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:04.510936image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:06.078325image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:07.636254image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:49.951446image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:51.433732image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:52.826049image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:54.316748image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:55.763965image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:57.181283image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:58.888642image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:00.333770image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:01.730283image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:03.261157image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:04.634886image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:06.212738image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:07.764765image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:50.081110image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:51.539265image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:52.936471image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:54.434377image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:55.883299image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:57.307622image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:59.014099image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:00.440795image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:01.863390image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:03.376169image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:04.773695image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:06.329428image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:07.864591image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:50.191602image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:51.655028image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:53.034557image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:54.528466image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:55.967846image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:57.422693image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:59.127531image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:00.537938image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:01.997795image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:03.462750image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:04.877014image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:06.435984image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:08.186982image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:50.313150image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:51.763494image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:53.146524image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:54.643338image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:56.077523image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:57.538252image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:59.242622image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:00.645200image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:02.115979image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:03.572152image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:04.986470image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:06.540819image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:08.296539image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:50.430725image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:51.850911image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:53.264418image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:54.737560image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:56.203441image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:57.641902image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:59.334453image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:00.756128image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:02.241021image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:03.672959image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:05.097116image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:06.641155image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:08.397242image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:50.523794image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:51.954252image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:53.366281image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:54.854649image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:56.310325image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:57.745413image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:59.428114image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:00.853545image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:02.350850image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:03.775473image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:05.216062image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:06.737430image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:08.499810image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:50.616437image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:52.059973image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:53.466878image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:54.977838image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:56.433501image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:57.869403image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:59.534321image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:00.942678image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:02.475522image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:03.881377image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:05.351086image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:06.845869image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:08.600419image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:50.724662image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:52.154217image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:53.570062image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:55.093290image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:56.531336image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:57.964670image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:59.640836image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:01.039993image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:02.580197image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:03.966488image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:05.455988image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:06.957252image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:08.714218image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:50.856981image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:52.258472image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:53.688584image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:55.215615image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:56.628202image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:58.319202image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:59.745988image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:01.154366image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:02.698271image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:04.077686image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:05.565028image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:07.072417image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:08.836827image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:50.990439image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:52.360089image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:53.821359image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:55.322485image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:56.739357image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:58.418587image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:11:59.862673image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:01.276639image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:02.807636image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:04.183936image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:05.697089image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-07-29T17:12:07.179614image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Correlations

2024-07-29T17:12:13.426098image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
AQICardiovascularCasesHealthImpactClassHealthImpactScoreHospitalAdmissionsHumidityNO2O3PM10PM2_5RespiratoryCasesSO2TemperatureWindSpeed
AQI1.0000.0100.3180.716-0.012-0.0040.0080.0020.0230.0060.008-0.0070.004-0.019
CardiovascularCases0.0101.0000.0000.003-0.039-0.025-0.0070.0030.0170.021-0.007-0.0060.0070.001
HealthImpactClass0.3180.0001.000-0.6610.0220.001-0.100-0.122-0.133-0.168-0.016-0.0160.0070.009
HealthImpactScore0.7160.003-0.6611.000-0.030-0.0050.1040.1430.1600.1800.0150.009-0.011-0.027
HospitalAdmissions-0.012-0.0390.022-0.0301.000-0.007-0.002-0.012-0.011-0.0290.005-0.0110.008-0.007
Humidity-0.004-0.0250.001-0.005-0.0071.000-0.0110.004-0.0170.0060.0080.001-0.0000.021
NO20.008-0.007-0.1000.104-0.002-0.0111.000-0.0150.0080.0050.021-0.0200.007-0.002
O30.0020.003-0.1220.143-0.0120.004-0.0151.000-0.0040.006-0.006-0.004-0.001-0.003
PM100.0230.017-0.1330.160-0.011-0.0170.008-0.0041.000-0.013-0.008-0.007-0.017-0.019
PM2_50.0060.021-0.1680.180-0.0290.0060.0050.006-0.0131.0000.0260.016-0.0020.009
RespiratoryCases0.008-0.007-0.0160.0150.0050.0080.021-0.006-0.0080.0261.0000.0120.008-0.008
SO2-0.007-0.006-0.0160.009-0.0110.001-0.020-0.004-0.0070.0160.0121.000-0.023-0.002
Temperature0.0040.0070.007-0.0110.008-0.0000.007-0.001-0.017-0.0020.008-0.0231.0000.001
WindSpeed-0.0190.0010.009-0.027-0.0070.021-0.002-0.003-0.0190.009-0.008-0.0020.0011.000

Missing values

2024-07-29T17:12:09.020344image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-29T17:12:09.220469image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

AQIPM10PM2_5NO2SO2O3TemperatureHumidityWindSpeedRespiratoryCasesCardiovascularCasesHospitalAdmissionsHealthImpactScoreHealthImpactClass
0187.270065295.85302713.0385616.63926366.16114854.6242795.15033584.4243476.13775575197.2440410.0
1475.357147246.2547009.98449716.31832790.499519169.6217351.54337846.8514144.5214211020100.0000000.0
2365.99697984.44319223.11134096.31781017.8758519.0067941.16948317.80697611.1573841330100.0000000.0
3299.32925421.02060914.27340381.23440648.32361693.16103421.92527699.47337315.302500881100.0000000.0
478.00932316.987667152.111618121.23545890.866165241.7951359.21751724.90683714.53473490195.1826400.0
577.99726136.11344597.11324387.76956232.261208136.999710-1.44178132.6359024.675127135270.3614881.0
629.041805174.23057668.578415186.81536996.76641844.98239534.37859324.6793046.610047102265.8199461.0
7433.088074278.62902883.673782106.9479459.707749131.56601033.70743640.37315817.3766441181100.0000000.0
8300.557495149.023026185.789352138.74520990.26712059.40987833.12314636.03521314.464875864100.0000000.0
9354.036285252.883652182.150360179.29705844.521214117.9574369.53724764.09920514.2538781351100.0000000.0
AQIPM10PM2_5NO2SO2O3TemperatureHumidityWindSpeedRespiratoryCasesCardiovascularCasesHospitalAdmissionsHealthImpactScoreHealthImpactClass
580150.07749961.953949195.157867160.77526920.680487200.07115216.19176395.7046517.37246075096.1906740.0
5802135.858795290.94622874.23859464.09793134.131260167.559235-1.89869260.6338771.748650870100.0000003.0
5803407.9779057.5012344.51233091.65309922.857208164.69093326.79866049.82620219.1768251462100.0000003.0
5804189.157806235.73465029.528698144.25711162.544201153.24903918.01404242.36085515.025267931100.0000003.0
580544.19848396.4109885.26774086.6702423.955073283.16546611.99537334.12431712.414963134159.9150011.0
5806171.11276211.246387197.984634158.64311217.743679280.37091137.35932261.7076424.0971291452100.0000004.0
5807490.691681275.34075955.774170132.33686829.334724108.04349534.53254321.5285556.682549862100.0000003.0
5808314.84179741.892700184.70855782.10582068.334579105.56850422.97556392.7256242.8896981223100.0000001.0
5809208.080475165.533783199.177261100.79638787.586487166.46954336.09062225.83628710.722392623100.0000004.0
581083.26925782.216263119.968246193.44068979.84917428.68188518.23909077.09619116.410320142281.6682970.0